4.5 Review

UAS-Based Plant Phenotyping for Research and Breeding Applications

Journal

PLANT PHENOMICS
Volume 2021, Issue -, Pages -

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.34133/2021/9840192

Keywords

-

Funding

  1. Iowa Soybean Association
  2. Plant Sciences Institute
  3. Bayer Chair in Soybean Breeding
  4. R.F. Baker Center for Plant Breeding
  5. USDA National Institute of Food and Agriculture (NIFA) Food and Agriculture Cyberinformatics Tools (FACT) [2019-67021-29938]
  6. NSF [SCC-1952045, DBI-1265383, DBI-1743442]
  7. USDA-CRIS [IOW04714]
  8. CyVerse
  9. USDA NIFA [2020-67021-31528, 2020-68013-30934]
  10. CREST Program [JPMJCR1512]
  11. SICORP Program of the Japan Science and Technology Agency, Japan [JPMJSC16H2]

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Unmanned aircraft systems (UAS) are a powerful tool for plant phenotyping, with advantages in cost, ease of use, sensor payload diversity, and connectivity. This paper reviews the current status of data deployment, collection, and analysis from UAS-based phenotyping platforms, discussing technical challenges and future trends. The review aims to provide insights for plant science practitioners interested in utilizing UAS-based imaging for phenotyping in research and breeding.
Unmanned aircraft system (UAS) is a particularly powerful tool for plant phenotyping, due to reasonable cost of procurement and deployment, ease and flexibility for control and operation, ability to reconfigure sensor payloads to diversify sensing, and the ability to seamlessly fit into a larger connected phenotyping network. These advantages have expanded the use of UAS-based plant phenotyping approach in research and breeding applications. This paper reviews the state of the art in the deployment, collection, curation, storage, and analysis of data from UAS-based phenotyping platforms. We discuss pressing technical challenges, identify future trends in UAS-based phenotyping that the plant research community should be aware of, and pinpoint key plant science and agronomic questions that can be resolved with the next generation of UAS-based imaging modalities and associated data analysis pipelines. This review provides a broad account of the state of the art in UAS-based phenotyping to reduce the barrier to entry to plant science practitioners interested in deploying this imaging modality for phenotyping in plant breeding and research areas.

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